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## Index Terms (2006)

Citations: | 1 - 0 self |

### Citations

8873 |
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.
- Pearl
- 1988
(Show Context)
Citation Context ...SIAN NETWORKS A. Graphical Representation of Probability Distribution Bayesian networks (BNs) are a representation, via a directed acyclic graph, of the dependencies between a set of random variables =-=[12]-=-. The network represents causal relationships between the variables. There is one node for each variable and a directed edge from node A to node B represents that the variable at node A “causes” what ... |

1582 |
Graphical Models.
- Lauritzen
- 1996
(Show Context)
Citation Context ...that takes account of the relationships between parameters. A common technique in stochastic modelling for this situation is the use of graphical models to specify the relationships between variables =-=[4]-=-. A Bayesian Network (BN) is a type of graphical model. The advantages of using BNs is that they facilitate the clear specification of the relationships between system parameters, and they also lead t... |

183 |
Core Team, R: A Language and Environment for
- Development
- 2011
(Show Context)
Citation Context ...lternative methods. For this work, adaptive rejection metropolis sampling (ARMS) was used to simulate from all posterior distributions. This was implemented using the arms [13] software package for R =-=[14]-=-. B. Reliable Clustered Computing using the Complete BN Assume also that nτk observations of repair times for the kth level are observed. This example uses four recovery levels, so k = 4. The full BN ... |

48 | Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation, - Müller, Sanso, et al. - 2004 |

38 |
The philosophy of statistics.
- Lindley
- 2000
(Show Context)
Citation Context ...this type of analysis is to gain the ability to make decisions about the system. Here we use decision theory, the natural partner to Bayesian statistical methods for decision making under uncertainty =-=[16]-=-. This requires us to specify a function, the utility function, that describes the worth of different outcomes of a decision to us. The outcome depends on unknown quantities. We take the action that m... |

36 | Graphical models for genetic analyses
- Lauritzen, Sheehan
- 2003
(Show Context)
Citation Context ...stical inference. The versatility of BNs is becoming increasingly recognised in the field of reliability [5]–[9]. BNs are also seeing increasing use in other fields, such as the modelling of genetics =-=[10]-=- and financial systems [11]. This paper is structured as follows. Section III describes the segregated failure model for availability prediction we discuss and introduces the example system. Section I... |

17 | A continuous-time bayesian network reliability modeling and analysis framework.
- Boudali, Dugan
- 2006
(Show Context)
Citation Context ...tem parameters, and they also lead to significant computational savings when implementing statistical inference. The versatility of BNs is becoming increasingly recognised in the field of reliability =-=[5]-=-–[9]. BNs are also seeing increasing use in other fields, such as the modelling of genetics [10] and financial systems [11]. This paper is structured as follows. Section III describes the segregated f... |

16 |
Assessing the Reliability of Diverse FaultTolerant Software-based Systems
- Littlewood, Popov, et al.
(Show Context)
Citation Context ...ulated values of Td and taking percentiles. For example, the fifth and ninety-fifth percentile of the simulated sample give us a 90% prediction interval. For this data, the 90% prediction interval is =-=[8, 804]-=-. VII. DECISION MAKING UNDER UNCERTAINTY Having the joint probability distribution of all the variables that describe the availability of our system is not necessarily the goal of an analysis. Often, ... |

8 | Reliability estimation of safety-critical software-based systems using Bayesian networks - Helminen |

7 |
A Flexible Clustered Approach to High Availability
- Hughes-Fenchel
- 1997
(Show Context)
Citation Context ...ly to be successful. In this case, all intermediate levels can be omitted and the final recovery level may be applied. An example is the Lucent Technologies Reliable Clustered Computing (RCC) product =-=[1]-=-. The RCC product incorporates various recovery strategies to guarantee availability of commercial telecommunications systems. There is a considerable literature on availability estimation in the situ... |

4 |
Financial analysis using Bayesian networks.
- Gemela
- 2001
(Show Context)
Citation Context ...tility of BNs is becoming increasingly recognised in the field of reliability [5]–[9]. BNs are also seeing increasing use in other fields, such as the modelling of genetics [10] and financial systems =-=[11]-=-. This paper is structured as follows. Section III describes the segregated failure model for availability prediction we discuss and introduces the example system. Section IV models the example system... |

3 |
Availability evaluation of hardware/software systems with several recovery procedures.
- Vilkomir, Parnas, et al.
- 2005
(Show Context)
Citation Context ...ial telecommunications systems. There is a considerable literature on availability estimation in the situation where system parameters are known; our work is motivated by the recent model proposed in =-=[2]-=- and [3]. In this paper we address the situation where the value of some of the system parameters are unknown, but that some knowledge of this uncertainty is available. The uncertainty about parameter... |

2 | Method feasibility study: Bayesian networks - Hiirsalmi - 2000 |

1 |
failures model for availability evaluation of fault-tolerant systems
- “Segregated
- 2006
(Show Context)
Citation Context ...communications systems. There is a considerable literature on availability estimation in the situation where system parameters are known; our work is motivated by the recent model proposed in [2] and =-=[3]-=-. In this paper we address the situation where the value of some of the system parameters are unknown, but that some knowledge of this uncertainty is available. The uncertainty about parameter values ... |

1 |
HI: Simulation from distributions supported by nested hyperplanes: R package version 0.1-1
- Petris, Tardella, et al.
- 2005
(Show Context)
Citation Context ...is not the case, there are alternative methods. For this work, adaptive rejection metropolis sampling (ARMS) was used to simulate from all posterior distributions. This was implemented using the arms =-=[13]-=- software package for R [14]. B. Reliable Clustered Computing using the Complete BN Assume also that nτk observations of repair times for the kth level are observed. This example uses four recovery le... |